運動與休閒學院

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為配合我國社會變遷與體育發展及本校的轉型與發展，本學院於90年8月正式成立，並將原屬本校教育學院之體育學系（所）、運動競技學系、運動與休閒管理研究所調整成立運動與休閒學院，並於95學年度增設運動科學研究所：為提升本院競爭力於101學年度運動競技學系與運動科學研究所整併為「運動競技學系」，運動與休閒管理研究所與管理學院餐旅管理研究所整併為「運動休閒與餐旅管理研究所」。

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Author: search.filters.author.Füle János RóbertSubject: search.filters.subject.Acceleration

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    Applied Digital Sensor Technology in the Analysis of Different Intensity Movements and Sensor Placements
    (2014) 洋風; Füle János Róbert
    Purpose: The study analyzed and compared movement modes and cycles, intensity levels and digital sensor positions. The target was to identify characteristics of body movements that could pave the way to a healthy and sustainable life. Revelations of the study provide potential information for creating a new sporting equipment and experience. Method: The observation of locomotion was executed with three high-tech Inertial Measurement Units (IMUs) that were attached to participants at three locations (shoe, wrist and waist). IMU was the fusion of a gyroscope and an accelerometer. Walk, Run and Jump movements were compared at two intensities. Result: The statistical analysis revealed an applicable correlation between movements and intensities. The simple effects test resulted in non-significant interaction between movements and intensities. This interaction served as a tool for comparing movement patterns with each other. Body movements included a series of gait cycles. The gait cycle was determined by acceleration data. Peak to peak intervals caused by the heel strike of the left foot were compared. Angular velocity data of gait cycles were benchmarked among different intensities. As a result the Shoe IMU measured the angular velocity on the frontal Y axis and discovered a regular sequence of plantar and dorsiflexion. Conclusion: Angular velocity data from the frontal axis clearly identified the movement features of walking, running and jumping. The acceleration data on the sagittal plane could distinguish between low and high intensity movements. The acceleration and gyroscope data determined the intensities and the body movements. The locomotion of lower extremities was widely explored. Waist and wrist IMU data even enabled the estimation of energy expenditure. Analysis methods of sensor signals were subject to investigation. Application of multiple digital sensors provided a unique opportunity for new observations.